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Vantor · 3 hours ago

Lead Data Engineer

Westminster, CO

Full-time

Onsite

Senior Level, Lead/Staff

$107K/yr - $179K/yr

8+ years exp

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. The Lead Data Engineer will be responsible for building scalable data pipelines, developing reusable frameworks, and supporting analytics and product teams with timely data delivery.

Software

No H1B

U.S. Citizen Only

Responsibilities

Build scalable ingestion, transformation, and delivery pipelines for structured, semi-structured, and unstructured data

Develop reusable ELT/ETL frameworks with built-in validation, testing, and monitoring

Automate pipeline health checks, alerting, and SLA tracking for reliability and freshness

Partner with architects to optimize data storage, partitioning, and compute performance

Integrate CI/CD pipelines for data workflows (testing, deployment, rollback automation)

Collaborate with governance to capture lineage and embed validation as part of deployment

Support analytics, AI, and geospatial product teams with timely, trusted data delivery

Qualification

Data engineeringELT/ETL frameworksSQLPythonFivetranDbtCloud data platformsData modelingCommunication skillsCollaboration skills

Required

8+ years of experience in data engineering, analytics engineering, or data platform roles, with 2–3+ years in a technical lead capacity

Proven experience designing, building, and operating scalable data ingestion and transformation pipelines across structured, semi-structured, and unstructured data sources

Hands-on, production experience with Fivetran (or equivalent managed ingestion tools) for source system ingestion, connector management, schema evolution, and data reliability

Deep, hands-on experience with dbt for: Building modular, reusable transformation models, Implementing data tests, freshness checks, and documentation

Strong experience implementing modern ELT architectures on cloud data platforms such as Snowflake or Databricks

Demonstrated ability to build reusable data frameworks with embedded: Automated data quality validation and testing, Monitoring, alerting, and SLA tracking, Operational reliability and observability

Strong understanding of data modeling, partitioning, performance optimization, and cost management for large-scale analytical workloads

Experience partnering with data architecture and governance teams to: Capture lineage and metadata, Embed governance and quality checks into data pipelines, Enforce standards through code and automation

Experience supporting analytics, AI/ML, or geospatial product teams with timely, trusted, and production-ready data

Advanced proficiency in SQL and Python

Strong communication and collaboration skills, with the ability to lead technical design discussions and mentor engineers

Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience